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The ethics of artificial intelligence covers a broad range of topics within the field that are considered to have particular ethical stakes. [1] This includes algorithmic biases, fairness, [2] automated decision-making, accountability, privacy, and regulation.
Machine ethics (or machine morality, computational morality, or computational ethics) is a part of the ethics of artificial intelligence concerned with adding or ensuring moral behaviors of man-made machines that use artificial intelligence, otherwise known as artificial intelligent agents. [1]
From this higher body, following the recommendations made by the R&D Strategy on Artificial Intelligence of 2018, [133] the National Artificial Intelligence Strategy (2020) was developed, which already provided for actions concerning the governance of artificial intelligence and the ethical standards that should govern its use. This project was ...
Ethical humans create for artificial intelligence the guidelines we would create for any dangerous technology. We do not need a race toward AI anarchy.
Artificial Intelligence projects can have their ethical permissibility tested while designing, developing, and implementing an AI system. An AI framework such as the Care and Act Framework containing the SUM values—developed by the Alan Turing Institute tests projects in four main areas: [ 315 ] [ 316 ]
The philosophy of artificial intelligence is a branch of the philosophy of mind and the philosophy of computer science [1] that explores artificial intelligence and its implications for knowledge and understanding of intelligence, ethics, consciousness, epistemology, [2] and free will.
Robot ethics, sometimes known as "roboethics", concerns ethical problems that occur with robots, such as whether robots pose a threat to humans in the long or short run, whether some uses of robots are problematic (such as in healthcare or as 'killer robots' in war), and how robots should be designed such that they act 'ethically' (this last concern is also called machine ethics).
AI safety is an interdisciplinary field focused on preventing accidents, misuse, or other harmful consequences arising from artificial intelligence (AI) systems. It encompasses machine ethics and AI alignment, which aim to ensure AI systems are moral and beneficial, as well as monitoring AI systems for risks and enhancing their reliability.
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